GLO-Roots: an imaging platform enabling multidimensional characterization of soil-grown root systems

Plant multiscale networks: charting plant connectivity by multi-level analysis and imaging techniques

In multicellular and even single-celled organisms, individual components are interconnected at multiscale levels to produce enormously complex biological networks that help these systems maintain homeostasis for development and environmental adaptation. Systems biology studies initially adopted network analysis to explore how relationships between individual components give rise to complex biological processes. Network analysis has been applied to dissect the complex connectivity of mammalian brains across different scales in time and space in The Human Brain Project. In plant science, network analysis has similarly been applied to study the connectivity of plant components at the molecular, subcellular, cellular, organic, and organism levels. Analysis of these multiscale networks contributes to our understanding of how genotype determines phenotype. In this review, we summarized the theoretical framework of plant multiscale networks and introduced studies investigating plant networks by various experimental and computational modalities. We next discussed the currently available analytic methodologies and multi-level imaging techniques used to map multiscale networks in plants. Finally, we highlighted some of the technical challenges and key questions remaining to be addressed in this emerging field.

Optogenetics in Sinorhizobium meliloti Enables Spatial Control of Exopolysaccharide Production and Biofilm Structure

Microorganisms play a vital role in shaping the soil environment and enhancing plant growth by interacting with plant root systems. Because of the vast diversity of cell types involved, combined with dynamic and spatial heterogeneity, identifying the causal contribution of a defined factor, such as a microbial exopolysaccharide (EPS), remains elusive. Synthetic approaches that enable orthogonal control of microbial pathways are a promising means to dissect such complexity. Here we report the implementation of a synthetic, light-activated, transcriptional control platform using the blue-light responsive DNA binding protein EL222 in the nitrogen fixing soil bacterium Sinorhizobium meliloti. By fine-tuning the system, we successfully achieved optical control of an EPS production pathway without significant basal expression under noninducing (dark) conditions. Optical control of EPS recapitulated important behaviors such as a mucoid plate phenotype and formation of structured biofilms, enabling spatial control of biofilm structures in S. meliloti. The successful implementation of optically controlled gene expression in S. meliloti enables systematic investigation of how genotype and microenvironmental factors together shape phenotype in situ.

Root phenotyping: important and minimum information required for root modeling in crop plants

As plants cannot relocate, they require effective root systems for water and nutrient uptake. Root development plasticity enables plants to adapt to different environmental conditions. Research on improvements in crop root systems is limited in comparison with that in shoots as the former are difficult to image. Breeding more effective root systems is proposed as the "second green revolution". There are several recent publications on root system architecture (RSA), but the methods used to analyze the RSA have not been standardized. Here, we introduce traditional and current root-imaging methods and discuss root structure phenotyping. Some important root structures have not been standardized as roots are easily affected by rhizosphere conditions and exhibit greater plasticity than shoots; moreover, root morphology significantly varies even in the same genotype. For these reasons, it is difficult to define the ideal root systems for breeding. In this review, we introduce several types of software to analyze roots and identify important root parameters by modeling to simplify the root system characterization. These parameters can be extracted from photographs captured in the field. This modeling approach is applicable to various legacy root data stored in old or unpublished formats. Standardization of RSA data could help estimate root ideotypes.

Root phenotyping: important and minimum information required for root modeling in crop plants

As plants cannot relocate, they require effective root systems for water and nutrient uptake. Root development plasticity enables plants to adapt to different environmental conditions. Research on improvements in crop root systems is limited in comparison with that in shoots as the former are difficult to image. Breeding more effective root systems is proposed as the "second green revolution". There are several recent publications on root system architecture (RSA), but the methods used to analyze the RSA have not been standardized. Here, we introduce traditional and current root-imaging methods and discuss root structure phenotyping. Some important root structures have not been standardized as roots are easily affected by rhizosphere conditions and exhibit greater plasticity than shoots; moreover, root morphology significantly varies even in the same genotype. For these reasons, it is difficult to define the ideal root systems for breeding. In this review, we introduce several types of software to analyze roots and identify important root parameters by modeling to simplify the root system characterization. These parameters can be extracted from photographs captured in the field. This modeling approach is applicable to various legacy root data stored in old or unpublished formats. Standardization of RSA data could help estimate root ideotypes.

Modulation of plant root traits by nitrogen and phosphate: transporters, long-distance signaling proteins and peptides, and potential artificial traps

As sessile organisms, plants rely on their roots for anchorage and uptake of water and nutrients. Plant root is an organ showing extensive morphological and metabolic plasticity in response to diverse environmental stimuli including nitrogen (N) and phosphorus (P) nutrition/stresses. N and P are two essential macronutrients serving as not only cell structural components but also local and systemic signals triggering root acclimatory responses. Here, we mainly focused on the current advances on root responses to N and P nutrition/stresses regarding transporters as well as long-distance mobile proteins and peptides, which largely represent local and systemic regulators, respectively. Moreover, we exemplified some of the potential pitfalls in experimental design, which has been routinely adopted for decades. These commonly accepted methods may help researchers gain fundamental mechanistic insights into plant intrinsic responses, yet the output might lack strong relevance to the real situation in the context of natural and agricultural ecosystems. On this basis, we further discuss the established-and yet to be validated-improvements in experimental design, aiming at interpreting the data obtained under laboratory conditions in a more practical view.

Highlighting reactive oxygen species as multitaskers in root development

Reactive oxygen species (ROS) are naturally produced by several redox reactions during plant regular metabolism such as photosynthesis and respiration. Due to their chemical properties and high reactivity, ROS were initially described as detrimental for cells during oxidative stress. However, they have been further recognized as key players in numerous developmental and physiological processes throughout the plant life cycle. Recent studies report the important role of ROS as growth regulators during plant root developmental processes such as in meristem maintenance, in root elongation, and in lateral root, root hair, endodermis, and vascular tissue differentiation. All involve multifaceted interplays between steady-state levels of ROS with transcriptional regulators, phytohormones, and nutrients. In this review, we attempt to summarize recent findings about how ROS are involved in multiple stages of plant root development during cell proliferation, elongation, and differentiation.

Phenotyping Tomato Root Developmental Plasticity in Response to Salinity in Soil Rhizotrons

Plants have developed multiple strategies to respond to salt stress. In order to identify new traits related to salt tolerance, with potential breeding application, the research focus has recently been shifted to include root system architecture (RSA) and root plasticity. Using a simple but effective root phenotyping system containing soil (rhizotrons), RSA of several tomato cultivars and their response to salinity was investigated. We observed a high level of root plasticity of tomato seedlings under salt stress. The general root architecture was substantially modified in response to salt, especially with respect to position of the lateral roots in the soil. At the soil surface, where salt accumulates, lateral root emergence was most strongly inhibited. Within the set of tomato cultivars, H1015 was the most tolerant to salinity in both developmental stages studied. A significant correlation between several root traits and aboveground growth parameters was observed, highlighting a possible role for regulation of both ion content and root architecture in salt stress resilience.

What is quantitative plant biology?

Quantitative plant biology is an interdisciplinary field that builds on a long history of biomathematics and biophysics. Today, thanks to high spatiotemporal resolution tools and computational modelling, it sets a new standard in plant science. Acquired data, whether molecular, geometric or mechanical, are quantified, statistically assessed and integrated at multiple scales and across fields. They feed testable predictions that, in turn, guide further experimental tests. Quantitative features such as variability, noise, robustness, delays or feedback loops are included to account for the inner dynamics of plants and their interactions with the environment. Here, we present the main features of this ongoing revolution, through new questions around signalling networks, tissue topology, shape plasticity, biomechanics, bioenergetics, ecology and engineering. In the end, quantitative plant biology allows us to question and better understand our interactions with plants. In turn, this field opens the door to transdisciplinary projects with the society, notably through citizen science.

Comparative analysis reveals gravity is involved in the MIZ1-regulated root hydrotropism

Hydrotropism is the directed growth of roots toward the water found in the soil. However, mechanisms governing interactions between hydrotropism and gravitropism remain largely unclear. In this study, we found that an air system and an agar-sorbitol system induced only oblique water-potential gradients; an agar-glycerol system induced only vertical water-potential gradients; and a sand system established both oblique and vertical water-potential gradients. We employed obliquely oriented and vertically oriented experimental systems to study hydrotropism in Arabidopsis and tomato plants. Comparative analyses using different hydrotropic systems showed that gravity hindered the ability of roots to search for obliquely oriented water, whilst facilitating roots' search for vertically oriented water. We found that the gravitropism-deficient mutant aux1 showed enhanced hydrotropism in the oblique orientation but impaired root elongation towards water in the vertical orientation. The miz1 mutant exhibited deficient hydrotropism in the oblique orientation but normal root elongation towards water in the vertical orientation. Importantly, in contrast to miz1, the miz1/aux1 double mutant exhibited hydrotropic bending in the oblique orientation and attenuated root elongation towards water in the vertical orientation. Our results suggest that gravitropism is required for MIZ1-regulated root hydrotropism in both the oblique orientation and the vertical orientation, providing further insight into the role of gravity in root hydrotropism.

Linking Genes to Shape in Plants Using Morphometrics

A transition from qualitative to quantitative descriptors of morphology has been facilitated through the growing field of morphometrics, representing the conversion of shapes and patterns into numbers. The analysis of plant form at the macromorphological scale using morphometric approaches quantifies what is commonly referred to as a phenotype. Quantitative phenotypic analysis of individuals with contrasting genotypes in turn provides a means to establish links between genes and shapes. The path from a gene to a morphological phenotype is, however, not direct, with instructive information progressing both across multiple scales of biological complexity and through nonintuitive feedback, such as mechanical signals. In this review, we explore morphometric approaches used to perform whole-plant phenotyping and quantitative approaches in capture processes in the mesoscales, which bridge the gaps between genes and shapes in plants. Quantitative frameworks involving both the computational simulation and the discretization of data into networks provide a putative path to predicting emergent shape from underlying genetic programs.

Affordable and robust phenotyping framework to analyse root system architecture of soil-grown plants

The phenotypic analysis of root system growth is important to inform efforts to enhance plant resource acquisition from soils; however, root phenotyping remains challenging because of the opacity of soil, requiring systems that facilitate root system visibility and image acquisition. Previously reported systems require costly or bespoke materials not available in most countries, where breeders need tools to select varieties best adapted to local soils and field conditions. Here, we report an affordable soil-based growth (rhizobox) and imaging system to phenotype root development in glasshouses or shelters. All components of the system are made from locally available commodity components, facilitating the adoption of this affordable technology in low-income countries. The rhizobox is large enough (approximately 6000 cm² of visible soil) to avoid restricting vertical root system growth for most if not all of the life cycle, yet light enough (approximately 21 kg when filled with soil) for routine handling. Support structures and an imaging station, with five cameras covering the whole soil surface, complement the rhizoboxes. Images are acquired via the Phenotiki sensor interface, collected, stitched and analysed. Root system architecture (RSA) parameters are quantified without intervention. The RSAs of a dicot species (Cicer arietinum, chickpea) and a monocot species (Hordeum vulgare, barley), exhibiting contrasting root systems, were analysed. Insights into root system dynamics during vegetative and reproductive stages of the chickpea life cycle were obtained. This affordable system is relevant for efforts in Ethiopia and other low- and middle-income countries to enhance crop yields and climate resilience sustainably.

QTG-Finder2: A Generalized Machine-Learning Algorithm for Prioritizing QTL Causal Genes in Plants

Linkage mapping has been widely used to identify quantitative trait loci (QTL) in many plants and usually requires a time-consuming and labor-intensive fine mapping process to find the causal gene underlying the QTL. Previously, we described QTG-Finder, a machine-learning algorithm to rationally prioritize candidate causal genes in QTLs. While it showed good performance, QTG-Finder could only be used in Arabidopsis and rice because of the limited number of known causal genes in other species. Here we tested the feasibility of enabling QTG-Finder to work on species that have few or no known causal genes by using orthologs of known causal genes as the training set. The model trained with orthologs could recall about 64% of Arabidopsis and 83% of rice causal genes when the top 20% ranked genes were considered, which is similar to the performance of models trained with known causal genes. The average precision was 0.027 for Arabidopsis and 0.029 for rice. We further extended the algorithm to include polymorphisms in conserved non-coding sequences and gene presence/absence variation as additional features. Using this algorithm, QTG-Finder2, we trained and cross-validated Sorghum bicolor and Setaria viridis models. The S. bicolor model was validated by causal genes curated from the literature and could recall 70% of causal genes when the top 20% ranked genes were considered. In addition, we applied the S. viridis model and public transcriptome data to prioritize a plant height QTL and identified 13 candidate genes. QTL-Finder2 can accelerate the discovery of causal genes in any plant species and facilitate agricultural trait improvement.

Root morphology and exudate availability are shaped by particle size and chemistry in Brachypodium distachyon

Root morphology and exudation define a plants' sphere of influence in soils. In turn, soil characteristics influence plant growth, morphology, root microbiome, and rhizosphere chemistry. Collectively, all these parameters have significant implications on the major biogeochemical cycles, crop yield, and ecosystem health. However, how plants are shaped by the physiochemistry of soil particles is still not well understood. We explored how particle size and chemistry of growth substrates affect root morphology and exudation of a model grass. We grew Brachypodium distachyon in glass beads with various sizes (0.5, 1, 2, 3 mm), as well as in sand (0.005, 0.25, 4 mm) and in clay (4 mm) particles and in particle-free hydroponic medium. Plant morphology, root weight, and shoot weight were measured. We found that particle size significantly influenced root fresh weight and root length, whereas root number and shoot weight remained constant. Next, plant exudation profiles were analyzed with mass spectrometry imaging and liquid chromatography-mass spectrometry. Mass spectrometry imaging suggested that both, root length and number shape root exudation. Exudate profiles were comparable for plants growing in glass beads or sand with various particles sizes, but distinct for plants growing in clay for in situ exudate collection. Clay particles were found to sorb 20% of compounds exuded by clay-grown plants, and 70% of compounds from a defined exudate medium. The sorbed compounds belonged to a range of chemical classes, among them nucleosides, organic acids, sugars, and amino acids. Some of the sorbed compounds could be desorbed by a rhizobacterium (Pseudomonas fluorescens WCS415), supporting its growth. This study demonstrates the effect of different characteristics of particles on root morphology, plant exudation and availability of nutrients to microorganisms. These findings further support the critical importance of the physiochemical properties of soils when investigating plant morphology, plant chemistry, and plant-microbe interactions.

The impact of the rhizobia-legume symbiosis on host root system architecture

Legumes form symbioses with rhizobia to fix N2 in root nodules to supplement their nitrogen (N) requirements. Many studies have shown how symbioses affect the shoot, but far less is understood about how they modify root development and root system architecture (RSA). RSA is the distribution of roots in space and over time. RSA reflects host resource allocation into below-ground organs and patterns of host resource foraging underpinning its resource acquisition capacity. Recent studies have revealed a more comprehensive relationship between hosts and symbionts: the latter can affect host resource acquisition for phosphate and iron, and the symbiont's production of plant growth regulators can enhance host resource flux and abundance. We review the current understanding of the effects of rhizobia-legume symbioses on legume root systems. We focus on resource acquisition and allocation within the host to conceptualize the effect of symbioses on RSA, and highlight opportunities for new directions of research.

Soybean Root System Architecture Trait Study through Genotypic, Phenotypic, and Shape-Based Clusters

We report a root system architecture (RSA) traits examination of a larger scale soybean accession set to study trait genetic diversity. Suffering from the limitation of scale, scope, and susceptibility to measurement variation, RSA traits are tedious to phenotype. Combining 35,448 SNPs with an imaging phenotyping platform, 292 accessions (replications = 14) were studied for RSA traits to decipher the genetic diversity. Based on literature search for root shape and morphology parameters, we used an ideotype-based approach to develop informative root (iRoot) categories using root traits. The RSA traits displayed genetic variability for root shape, length, number, mass, and angle. Soybean accessions clustered into eight genotype- and phenotype-based clusters and displayed similarity. Genotype-based clusters correlated with geographical origins. SNP profiles indicated that much of US origin genotypes lack genetic diversity for RSA traits, while diverse accession could infuse useful genetic variation for these traits. Shape-based clusters were created by integrating convolution neural net and Fourier transformation methods, enabling trait cataloging for breeding and research applications. The combination of genetic and phenotypic analyses in conjunction with machine learning and mathematical models provides opportunities for targeted root trait breeding efforts to maximize the beneficial genetic diversity for future genetic gains.

CEP receptor signalling controls root system architecture in Arabidopsis and Medicago

Root system architecture (RSA) influences the effectiveness of resources acquisition from soils but the genetic networks that control RSA remain largely unclear. We used rhizoboxes, X-ray computed tomography, grafting, auxin transport measurements and hormone quantification to demonstrate that Arabidopsis and Medicago CEP (C-TERMINALLY ENCODED PEPTIDE)-CEP RECEPTOR signalling controls RSA, the gravitropic set-point angle (GSA) of lateral roots (LRs), auxin levels and auxin transport. We showed that soil-grown Arabidopsis and Medicago CEP receptor mutants have a narrower RSA, which results from a steeper LR GSA. Grafting showed that CEPR1 in the shoot controls GSA. CEP receptor mutants exhibited an increase in rootward auxin transport and elevated shoot auxin levels. Consistently, the application of auxin to wild-type shoots induced a steeper GSA and auxin transport inhibitors counteracted the CEP receptor mutant's steep GSA phenotype. Concordantly, CEP peptides increased GSA and inhibited rootward auxin transport in wild-type but not in CEP receptor mutants. The results indicated that CEP-CEP receptor-dependent signalling outputs in Arabidopsis and Medicago control overall RSA, LR GSA, shoot auxin levels and rootward auxin transport. We propose that manipulating CEP signalling strength or CEP receptor downstream targets may provide means to alter RSA.

Coping With Water Limitation: Hormones That Modify Plant Root Xylem Development

Periods of drought, that threaten crop production, are expected to become more prominent in large parts of the world, making it necessary to explore all aspects of plant growth and development, to breed, modify and select crops adapted to such conditions. One such aspect is the xylem, where influencing the size and number of the water-transporting xylem vessels, may impact on hydraulic conductance and drought tolerance. Here, we focus on how plants adjust their root xylem as a response to reduced water availability. While xylem response has been observed in a wide array of species, most of our knowledge on the molecular mechanisms underlying xylem plasticity comes from studies on the model plant Arabidopsis thaliana. When grown under water limiting conditions, Arabidopsis rapidly adjusts its development to produce more xylem strands with altered identity in an abscisic acid (ABA) dependent manner. Other hormones such as auxin and cytokinin are essential for vascular patterning and differentiation. Their balance can be perturbed by stress, as evidenced by the effects of enhanced jasmonic acid signaling, which results in similar xylem developmental alterations as enhanced ABA signaling. Furthermore, brassinosteroids and other signaling molecules involved in drought tolerance can also impact xylem development. Hence, a multitude of signals affect root xylem properties and, potentially, influence survival under water limiting conditions. Here, we review the likely entangled signals that govern root vascular development, and discuss the importance of taking root anatomical traits into account when breeding crops for enhanced resilience toward changes in water availability.

Novel Imaging Modalities Shedding Light on Plant Biology: Start Small and Grow Big

The acquisition of quantitative information on plant development across a range of temporal and spatial scales is essential to understand the mechanisms of plant growth. Recent years have shown the emergence of imaging methodologies that enable the capture and analysis of plant growth, from the dynamics of molecules within cells to the measurement of morphometricand physiological traits in field-grown plants. In some instances, these imaging methods can be parallelized across multiple samples to increase throughput. When high throughput is combined with high temporal and spatial resolution, the resulting image-derived data sets could be combined with molecular large-scale data sets to enable unprecedented systems-level computational modeling. Such image-driven functional genomics studies may be expected to appear at an accelerating rate in the near future given the early success of the foundational efforts reviewed here. We present new imaging modalities and review how they have enabled a better understanding of plant growth from the microscopic to the macroscopic scale.

Salt Tolerance Mechanisms of Plants

Crop loss due to soil salinization is an increasing threat to agriculture worldwide. This review provides an overview of cellular and physiological mechanisms in plant responses to salt. We place cellular responses in a time- and tissue-dependent context in order to link them to observed phases in growth rate that occur in response to stress. Recent advances in phenotyping can now functionally or genetically link cellular signaling responses, ion transport, water management, and gene expression to growth, development, and survival. Halophytes, which are naturally salt-tolerant plants, are highlighted as success stories to learn from. We emphasize that (a) filling the major knowledge gaps in salt-induced signaling pathways, (b) increasing the spatial and temporal resolution of our knowledge of salt stress responses, (c) discovering and considering crop-specific responses, and (d) including halophytes in our comparative studies are all essential in order to take our approaches to increasing crop yields in saline soils to the next level.

Exploiting natural variation in root system architecture via genome-wide association studies

Root growth and development has become an important research topic for breeders and researchers based on a growing need to adapt plants to changing and more demanding environmental conditions worldwide. Over the last few years, genome-wide association studies (GWASs) became an important tool to identify the link between traits in the field and their genetic background. Here we give an overview of the current literature concerning GWASs performed on root system architecture (RSA) in plants. We summarize which root traits and approaches have been used for GWAS, mentioning their respective success rate towards a successful gene discovery. Furthermore, we zoom in on the current technical hurdles in root phenotyping and GWAS, and discuss future possibilities in this field of research.

Same same, but different: growth responses of primary and lateral roots

The root system architecture describes the shape and spatial arrangement of roots within the soil. Its spatial distribution depends on growth and branching rates as well as directional organ growth. The embryonic primary root gives rise to lateral (secondary) roots, and the ratio of both root types changes over the life span of a plant. Most studies have focused on the growth of primary roots and the development of lateral root primordia. Comparably less is known about the growth regulation of secondary root organs. Here, we review similarities and differences between primary and lateral root organ growth, and emphasize particularly how external stimuli and internal signals differentially integrate root system growth.

Micro-scale interactions between Arabidopsis root hairs and soil particles influence soil erosion

Soil is essential for sustaining life on land. Plant roots play a crucial role in stabilising soil and minimising erosion, although these mechanisms are still not completely understood. Consequently, identifying and breeding for plant traits to enhance erosion resistance is challenging. Root hair mutants in Arabidopsis thaliana were studied using three different quantitative methods to isolate their effect on root-soil cohesion. We present compelling evidence that micro-scale interactions of root hairs with surrounding soil increase soil cohesion and reduce erosion. Arabidopsis seedlings with root hairs were more difficult to detach from soil, compost and sterile gel media than those with hairless roots, and it was 10-times harder to erode soil from roots with than without hairs. We also developed a model that can consistently predict the impact root hairs make to soil erosion resistance. Our study thus provides new insight into the mechanisms by which roots maintain soil stability.

Sarah De Baets et al. investigate the effect of root hair abundance on root-substrate cohesion and experimental soil erosion in Arabidopsis. They find that plants with root hairs are more difficult to detach from soil and are better able to prevent soil erosion than root hairless plants and present a model to predict the impact of root hairs on soil erosion resistance.

Targeting Root Ion Uptake Kinetics to Increase Plant Productivity and Nutrient Use Efficiency

Root system architecture has received increased attention in recent years; however, significant knowledge gaps remain for physiological phenes, or units of phenotype, that have been relatively less studied. Ion uptake kinetics studies have been invaluable in uncovering distinct nutrient uptake systems in plants with the use of Michaelis-Menten kinetic modeling. This review outlines the theoretical framework behind ion uptake kinetics, provides a meta-analysis for macronutrient uptake parameters, and proposes new strategies for using uptake kinetics parameters as selection criteria for breeding crops with improved resource acquisition capability. Presumably, variation in uptake kinetics is caused by variation in type and number of transporters, assimilation machinery, and anatomical features that can vary greatly within and among species. Critically, little is known about what determines transporter properties at the molecular level or how transporter properties scale to the entire root system. A meta-analysis of literature containing measures of crop nutrient uptake kinetics provides insights about the need for standardization of reporting, the differences among crop species, and the relationships among various uptake parameters and experimental conditions. Therefore, uptake kinetics parameters are proposed as promising target phenes that integrate several processes for functional phenomics and genetic analysis, which will lead to a greater understanding of this fundamental plant process. Exploiting this genetic and phenotypic variation has the potential to greatly advance breeding efforts for improved nutrient use efficiency in crops.

Building customizable auto-luminescent luciferase-based reporters in plants

Bioluminescence is a powerful biological signal that scientists have repurposed as a reporter for gene expression in plants and animals. However, there are downsides associated with the need to provide a substrate to these reporters, including its high cost and non-uniform tissue penetration. In this work we reconstitute a fungal bioluminescence pathway (FBP) in planta using a composable toolbox of parts. We demonstrate that the FBP can create luminescence across various tissues in a broad range of plants without external substrate addition. We also show how our toolbox can be used to deploy the FBP in planta to build auto-luminescent reporters for the study of gene-expression and hormone fluxes. A low-cost imaging platform for gene expression profiling is also described. These experiments lay the groundwork for future construction of programmable auto-luminescent plant traits, such as light driven plant-pollinator interactions or light emitting plant-based sensors.

Litterbox-A gnotobiotic Zeolite-Clay System to Investigate Arabidopsis-Microbe Interactions

Plants are colonised by millions of microorganisms representing thousands of species withvarying effects on plant growth and health. The microbial communities found on plants arecompositionally consistent and their overall positive effect on the plant is well known. However,the effects of individual microbiota members on plant hosts and vice versa, as well as the underlyingmechanisms, remain largely unknown. Here, we describe "Litterbox", a highly controlled system toinvestigate plant-microbe interactions. Plants were grown gnotobiotically, otherwise sterile, onzeolite-clay, a soil replacement that retains enough moisture to avoid subsequent watering.Litterbox-grown plants resemble greenhouse-grown plants more closely than agar-grown plantsand exhibit lower leaf epiphyte densities (106 cfu/g), reflecting natural conditions. Apolydimethylsiloxane (PDMS) sheet was used to cover the zeolite, significantly lowering thebacterial load in the zeolite and rhizosphere. This reduced the likelihood of potential systemicresponses in leaves induced by microbial rhizosphere colonisation. We present results of exampleexperiments studying the transcriptional responses of leaves to defined microbiota members andthe spatial distribution of bacteria on leaves. We anticipate that this versatile and affordable plantgrowth system will promote microbiota research and help in elucidating plant-microbe interactionsand their underlying mechanisms.

The dynamic nature and regulation of the root clock

Plants explore the soil by continuously expanding their root system, a process that depends on the production of lateral roots (LRs). Sites where LRs can be produced are specified in the primary root axis through a pre-patterning mechanism, determined by a biological clock that is coordinated by temporal signals and positional cues. This ‘root clock’ generates an oscillatory signal that is translated into a developmental cue to specify a set of founder cells for LR formation. In this Review, we summarize recent findings that shed light on the mechanisms underlying the oscillatory signal and discuss how a periodic signal contributes to the conversion of founder cells into LR primordia. We also provide an overview of the phases of the root clock that may be influenced by endogenous factors, such as the plant hormone auxin, and by exogenous environmental cues. Finally, we discuss additional aspects of the root-branching process that act independently of the root clock.

SoilCam: A Fully Automated Minirhizotron using Multispectral Imaging for Root Activity Monitoring

A minirhizotron is an in situ root imaging system that captures components of root system architecture dynamics over time. Commercial minirhizotrons are expensive, limited to white-light imaging, and often need human intervention. The implementation of a minirhizotron needs to be low cost, automated, and customizable to be effective and widely adopted. We present a newly designed root imaging system called SoilCam that addresses the above mentioned limitations. The imaging system is multi-modal, i.e., it supports both conventional white-light and multispectral imaging, with fully automated operations for long-term in-situ monitoring using wireless control and access. The system is capable of taking 360° images covering the entire area surrounding the tube. The image sensor can be customized depending on the spectral imaging requirements. The maximum achievable image quality of the system is 8 MP (Mega Pixel)/picture, which is equivalent to a 2500 DPI (dots per inch) image resolution. The length of time in the field can be extended with a rechargeable battery and solar panel connectivity. Offline image-processing software, with several image enhancement algorithms to eliminate motion blur and geometric distortion and to reconstruct the 360° panoramic view, is also presented. The system is tested in the field by imaging canola roots to show the performance advantages over commercial systems.

Computer vision and machine learning enabled soybean root phenotyping pipeline

BACKGROUND

Root system architecture (RSA) traits are of interest for breeding selection; however, measurement of these traits is difficult, resource intensive, and results in large variability. The advent of computer vision and machine learning (ML) enabled trait extraction and measurement has renewed interest in utilizing RSA traits for genetic enhancement to develop more robust and resilient crop cultivars. We developed a mobile, low-cost, and high-resolution root phenotyping system composed of an imaging platform with computer vision and ML based segmentation approach to establish a seamless end-to-end pipeline - from obtaining large quantities of root samples through image based trait processing and analysis.

RESULTS

This high throughput phenotyping system, which has the capacity to handle hundreds to thousands of plants, integrates time series image capture coupled with automated image processing that uses optical character recognition (OCR) to identify seedlings via barcode, followed by robust segmentation integrating convolutional auto-encoder (CAE) method prior to feature extraction. The pipeline includes an updated and customized version of the Automatic Root Imaging Analysis (ARIA) root phenotyping software. Using this system, we studied diverse soybean accessions from a wide geographical distribution and report genetic variability for RSA traits, including root shape, length, number, mass, and angle.

CONCLUSIONS

This system provides a high-throughput, cost effective, non-destructive methodology that delivers biologically relevant time-series data on root growth and development for phenomics, genomics, and plant breeding applications. This phenotyping platform is designed to quantify root traits and rank genotypes in a common environment thereby serving as a selection tool for use in plant breeding. Root phenotyping platforms and image based phenotyping are essential to mirror the current focus on shoot phenotyping in breeding efforts.

Computer vision and machine learning enabled soybean root phenotyping pipeline

BACKGROUND

Root system architecture (RSA) traits are of interest for breeding selection; however, measurement of these traits is difficult, resource intensive, and results in large variability. The advent of computer vision and machine learning (ML) enabled trait extraction and measurement has renewed interest in utilizing RSA traits for genetic enhancement to develop more robust and resilient crop cultivars. We developed a mobile, low-cost, and high-resolution root phenotyping system composed of an imaging platform with computer vision and ML based segmentation approach to establish a seamless end-to-end pipeline - from obtaining large quantities of root samples through image based trait processing and analysis.

RESULTS

This high throughput phenotyping system, which has the capacity to handle hundreds to thousands of plants, integrates time series image capture coupled with automated image processing that uses optical character recognition (OCR) to identify seedlings via barcode, followed by robust segmentation integrating convolutional auto-encoder (CAE) method prior to feature extraction. The pipeline includes an updated and customized version of the Automatic Root Imaging Analysis (ARIA) root phenotyping software. Using this system, we studied diverse soybean accessions from a wide geographical distribution and report genetic variability for RSA traits, including root shape, length, number, mass, and angle.

CONCLUSIONS

This system provides a high-throughput, cost effective, non-destructive methodology that delivers biologically relevant time-series data on root growth and development for phenomics, genomics, and plant breeding applications. This phenotyping platform is designed to quantify root traits and rank genotypes in a common environment thereby serving as a selection tool for use in plant breeding. Root phenotyping platforms and image based phenotyping are essential to mirror the current focus on shoot phenotyping in breeding efforts.

A Statistical Growth Property of Plant Root Architectures

Numerous types of biological branching networks, with varying shapes and sizes, are used to acquire and distribute resources. Here, we show that plant root and shoot architectures share a fundamental design property. We studied the spatial density function of plant architectures, which specifies the probability of finding a branch at each location in the 3-dimensional volume occupied by the plant. We analyzed 1645 root architectures from four species and discovered that the spatial density functions of all architectures are population-similar. This means that despite their apparent visual diversity, all of the roots studied share the same basic shape, aside from stretching and compression along orthogonal directions. Moreover, the spatial density of all architectures can be described as variations on a single underlying function: a Gaussian density truncated at a boundary of roughly three standard deviations. Thus, the root density of any architecture requires only four parameters to specify: the total mass of the architecture and the standard deviations of the Gaussian in the three (x, y, z) growth directions. Plant shoot architectures also follow this design form, suggesting that two basic plant transport systems may use similar growth strategies.

Molecular mechanisms mediating root hydrotropism: what we have observed since the rediscovery of hydrotropism

Roots display directional growth toward moisture in response to a water potential gradient. Root hydrotropism is thought to facilitate plant adaptation to continuously changing water availability. Hydrotropism has not been as extensively studied as gravitropism. However, comparisons of hydrotropic and gravitropic responses identified mechanisms that are unique to hydrotropism. Regulatory mechanisms underlying the hydrotropic response appear to differ among different species. We recently performed molecular and genetic analyses of root hydrotropism in Arabidopsis thaliana. In this review, we summarize the current knowledge of specific mechanisms mediating root hydrotropism in several plant species.

Developmental Responses to Water and Salinity in Root Systems

Roots provide the primary mechanism that plants use to absorb water and nutrients from their environment. These functions are dependent on developmental mechanisms that direct root growth and branching into regions of soil where these resources are relatively abundant. Water is the most limiting factor for plant growth, and its availability is determined by the weather, soil structure, and salinity. In this review, we define the developmental pathways that regulate the direction of growth and branching pattern of the root system, which together determine the expanse of soil from which a plant can access water. The ability of plants to regulate development in response to the spatial distribution of water is a focus of many recent studies and provides a model for understanding how biological systems utilize positional cues to affect signaling and morphogenesis. A better understanding of these processes will inform approaches to improve crop water use efficiency to more sustainably feed a growing population.

Lateral Root Formation in Arabidopsis: A Well-Ordered LRexit

Lateral roots (LRs) are crucial for increasing the surface area of root systems to explore heterogeneous soil environments. Major advances have recently been made in the model plant arabidopsis (Arabidopsis thaliana) to elucidate the cellular basis of LR development and the underlying gene regulatory networks (GRNs) that control the morphogenesis of the new root organ. This has provided a foundation for understanding the sophisticated adaptive mechanisms that regulate how plants pattern their root branching to match the spatial availability of resources such as water and nutrients in their external environment. We review new insights into the molecular, cellular, and environmental regulation of LR development in arabidopsis.

Long-term live-cell imaging approaches to study lateral root formation in Arabidopsis thaliana

Lateral roots comprise the majority of the branching root system and are important for acquiring nutrients and water from soil in addition to providing anchorage. Lateral roots develop post-embryonically from existing root parts and originate from a subset of specified pericycle cells (lateral root founder cells) located deep inside roots. Small numbers of these specified pericycle cells undergo several rounds of cell division to create a dome-shaped primordium, which eventually organizes a meristem, an essential region for plant growth with active cell division, and emerges from its parental root as a lateral root. Observing cellular and molecular processes for an extended time at various scales are crucial for understanding biological processes during organogenesis. Lateral root formation is an example of the successful application of live-cell imaging approaches to understand various aspects of developmental events in plants, including cell fate determination, cell proliferation, cell-to-cell interaction and cell wall modification. Here I review the recent progress in understanding the molecular mechanisms of lateral root formation and the contribution of live-cell imaging approaches.

Cytokinin functions as an asymmetric and anti-gravitropic signal in lateral roots

Directional organ growth allows the plant root system to strategically cover its surroundings. Intercellular auxin transport is aligned with the gravity vector in the primary root tips, facilitating downward organ bending at the lower root flank. Here we show that cytokinin signaling functions as a lateral root specific anti-gravitropic component, promoting the radial distribution of the root system. We performed a genome-wide association study and reveal that signal peptide processing of Cytokinin Oxidase 2 (CKX2) affects its enzymatic activity and, thereby, determines the degradation of cytokinins in natural Arabidopsis thaliana accessions. Cytokinin signaling interferes with growth at the upper lateral root flank and thereby prevents downward bending. Our interdisciplinary approach proposes that two phytohormonal cues at opposite organ flanks counterbalance each other's negative impact on growth, suppressing organ growth towards gravity and allow for radial expansion of the root system.

Three-Dimensional Time-Lapse Analysis Reveals Multiscale Relationships in Maize Root Systems with Contrasting Architectures

Understanding how an organism's phenotypic traits are conditioned by genetic and environmental variation is a central goal of biology. Root systems are one of the most important but poorly understood aspects of plants, largely due to the three-dimensional (3D), dynamic, and multiscale phenotyping challenge they pose. A critical gap in our knowledge is how root systems build in complexity from a single primary root to a network of thousands of roots that collectively compete for ephemeral, heterogeneous soil resources. We used time-lapse 3D imaging and mathematical modeling to assess root system architectures (RSAs) of two maize (Zea mays) inbred genotypes and their hybrid as they grew in complexity from a few to many roots. Genetically driven differences in root branching zone size and lateral branching densities along a single root, combined with differences in peak growth rate and the relative allocation of carbon resources to new versus existing roots, manifest as sharply distinct global RSAs over time. The 3D imaging of mature field-grown root crowns showed that several genetic differences in seedling architectures could persist throughout development and across environments. This approach connects individual and system-wide scales of root growth dynamics, which could eventually be used to predict genetic variation for complex RSAs and their functions.

Evaluating rice for salinity using pot-culture provides a systematic tolerance assessment at the seedling stage

BACKGROUND

Rice (Oryza sativa L.) is one of the major staple food crops consumed globally. However, rice production is severely affected by high salinity levels, particularly at the seedling stage. A good solution would be the development of an efficient screening methodology to identify genotypes possessing genes for salt tolerance.

RESULT

A new salinity tolerance screening technique using rice seedlings in pot-culture was tested. This method controls soil heterogeneity by using pure sand as a growth medium and minimizes unexpected extreme weather conditions with a movable shelter. Seventy-four rice genotypes were screened at three salinity treatments including high salt stress (electrical conductivity (EC) 12 dSm^- 1), moderate salt stress (EC 6 dSm^- 1), and control (no salt stress), imposed 1 week after emergence. Several shoot and root morpho-physiological traits were measured at 37 days after sowing. A wide range of variability was observed among genotypes for measured traits with root traits being identified as the best descriptors for tolerance to salt stress conditions. Salt stress response indices (SSRI) were used to classify the 74 rice genotypes; 7 genotypes (9.46%) were identified as salt sensitive, 27 (36.48%) each as low and moderately salt tolerant, and 13 (17.57%) as highly salt tolerant. Genotypes FED 473 and IR85427 were identified as the most salt tolerant and salt sensitive, respectively. These results were further confirmed by principal component analysis (PCA) for accuracy and reliability.

CONCLUSION

Although tolerant genotypes still need to be confirmed in field studies and tolerance mechanisms identified at the molecular level, information gained from this study could help rice breeders and other scientists to accelerate breeding by selecting appropriate donor parents, progenies and potential genotypes at early growth stages necessary for salinity tolerance research.

Evaluating rice for salinity using pot-culture provides a systematic tolerance assessment at the seedling stage

BACKGROUND

Rice (Oryza sativa L.) is one of the major staple food crops consumed globally. However, rice production is severely affected by high salinity levels, particularly at the seedling stage. A good solution would be the development of an efficient screening methodology to identify genotypes possessing genes for salt tolerance.

RESULT

A new salinity tolerance screening technique using rice seedlings in pot-culture was tested. This method controls soil heterogeneity by using pure sand as a growth medium and minimizes unexpected extreme weather conditions with a movable shelter. Seventy-four rice genotypes were screened at three salinity treatments including high salt stress (electrical conductivity (EC) 12 dSm^- 1), moderate salt stress (EC 6 dSm^- 1), and control (no salt stress), imposed 1 week after emergence. Several shoot and root morpho-physiological traits were measured at 37 days after sowing. A wide range of variability was observed among genotypes for measured traits with root traits being identified as the best descriptors for tolerance to salt stress conditions. Salt stress response indices (SSRI) were used to classify the 74 rice genotypes; 7 genotypes (9.46%) were identified as salt sensitive, 27 (36.48%) each as low and moderately salt tolerant, and 13 (17.57%) as highly salt tolerant. Genotypes FED 473 and IR85427 were identified as the most salt tolerant and salt sensitive, respectively. These results were further confirmed by principal component analysis (PCA) for accuracy and reliability.

CONCLUSION

Although tolerant genotypes still need to be confirmed in field studies and tolerance mechanisms identified at the molecular level, information gained from this study could help rice breeders and other scientists to accelerate breeding by selecting appropriate donor parents, progenies and potential genotypes at early growth stages necessary for salinity tolerance research.

Natural variation of BSK3 tunes brassinosteroid signaling to regulate root foraging under low nitrogen

Developmental plasticity of root system architecture is crucial for plant performance in nutrient-poor soils. Roots of plants grown under mild nitrogen (N) deficiency show a foraging response characterized by increased root length but mechanisms underlying this developmental plasticity are still elusive. By employing natural variation in Arabidopsis accessions, we show that the brassinosteroid (BR) signaling kinase BSK3 modulates root elongation under mild N deficiency. In particular, a proline to leucine substitution in the predicted kinase domain of BSK3 enhances BR sensitivity and signaling to increase the extent of root elongation. We further show that low N specifically upregulates transcript levels of the BR co-receptor BAK1 to activate BR signaling and stimulate root elongation. Altogether, our results uncover a role of BR signaling in root elongation under low N. The BSK3 alleles identified here provide targets for improving root growth of crops growing under limited N conditions.

Plant roots elongate under mild nitrogen deficiency as part of a foraging response that facilitates nutrient uptake. Here the authors show that natural variation in this response among Arabidopsis accessions depends on the brassinosteroid (BR) signaling kinase BSK3, which can enhance BR sensitivity and root growth.

Hydrogel-based transparent soils for root phenotyping in vivo

Root phenotypes are increasingly explored as predictors of crop performance but are still challenging to characterize. Media that mimic field conditions (e.g., soil, sand) are opaque to most forms of radiation, while transparent media do not provide field-relevant growing conditions and phenotypes. We describe here a "transparent soil" formed by the spherification of hydrogels of biopolymers. It is specifically designed to support root growth in the presence of air, water, and nutrients, and allows the time-resolved phenotyping of roots in vivo by both photography and microscopy. The roots developed by soybean plants in this medium are significantly more similar to those developed in real soil than those developed in hydroponic conditions and do not show signs of hypoxia. Lastly, we show that the granular nature and tunable properties of these hydrogel beads can be leveraged to investigate the response of roots to gradients in water availability and soil stiffness.

Water transport, perception, and response in plants

Sufficient water availability in the environment is critical for plant survival. Perception of water by plants is necessary to balance water uptake and water loss and to control plant growth. Plant physiology and soil science research have contributed greatly to our understanding of how water moves through soil, is taken up by roots, and moves to leaves where it is lost to the atmosphere by transpiration. Water uptake from the soil is affected by soil texture itself and soil water content. Hydraulic resistances for water flow through soil can be a major limitation for plant water uptake. Changes in water supply and water loss affect water potential gradients inside plants. Likewise, growth creates water potential gradients. It is known that plants respond to changes in these gradients. Water flow and loss are controlled through stomata and regulation of hydraulic conductance via aquaporins. When water availability declines, water loss is limited through stomatal closure and by adjusting hydraulic conductance to maintain cell turgor. Plants also adapt to changes in water supply by growing their roots towards water and through refinements to their root system architecture. Mechanosensitive ion channels, aquaporins, proteins that sense the cell wall and cell membrane environment, and proteins that change conformation in response to osmotic or turgor changes could serve as putative sensors. Future research is required to better understand processes in the rhizosphere during soil drying and how plants respond to spatial differences in water availability. It remains to be investigated how changes in water availability and water loss affect different tissues and cells in plants and how these biophysical signals are translated into chemical signals that feed into signaling pathways like abscisic acid response or organ development.

Multilab EcoFAB study shows highly reproducible physiology and depletion of soil metabolites by a model grass

There is a dynamic reciprocity between plants and their environment: soil physiochemical properties influence plant morphology and metabolism, and root morphology and exudates shape the environment surrounding roots. Here, we investigate the reproducibility of plant trait changes in response to three growth environments. We utilized fabricated ecosystem (EcoFAB) devices to grow the model grass Brachypodium distachyon in three distinct media across four laboratories: phosphate-sufficient and -deficient mineral media allowed assessment of the effects of phosphate starvation, and a complex, sterile soil extract represented a more natural environment with yet uncharacterized effects on plant growth and metabolism. Tissue weight and phosphate content, total root length, and root tissue and exudate metabolic profiles were consistent across laboratories and distinct between experimental treatments. Plants grown in soil extract were morphologically and metabolically distinct, with root hairs four times longer than with other growth conditions. Further, plants depleted half of the metabolites investigated from the soil extract. To interact with their environment, plants not only adapt morphology and release complex metabolite mixtures, but also selectively deplete a range of soil-derived metabolites. The EcoFABs utilized here generated high interlaboratory reproducibility, demonstrating their value in standardized investigations of plant traits.

Multilab EcoFAB study shows highly reproducible physiology and depletion of soil metabolites by a model grass

There is a dynamic reciprocity between plants and their environment: soil physiochemical properties influence plant morphology and metabolism, and root morphology and exudates shape the environment surrounding roots. Here, we investigate the reproducibility of plant trait changes in response to three growth environments. We utilized fabricated ecosystem (EcoFAB) devices to grow the model grass Brachypodium distachyon in three distinct media across four laboratories: phosphate-sufficient and -deficient mineral media allowed assessment of the effects of phosphate starvation, and a complex, sterile soil extract represented a more natural environment with yet uncharacterized effects on plant growth and metabolism. Tissue weight and phosphate content, total root length, and root tissue and exudate metabolic profiles were consistent across laboratories and distinct between experimental treatments. Plants grown in soil extract were morphologically and metabolically distinct, with root hairs four times longer than with other growth conditions. Further, plants depleted half of the metabolites investigated from the soil extract. To interact with their environment, plants not only adapt morphology and release complex metabolite mixtures, but also selectively deplete a range of soil-derived metabolites. The EcoFABs utilized here generated high interlaboratory reproducibility, demonstrating their value in standardized investigations of plant traits.

Phenotypic variation of cassava root traits and their responses to drought

PREMISE OF THE STUDY

The key to increased cassava production is balancing the trade-off between marketable roots and traits that drive nutrient and water uptake. However, only a small number of protocols have been developed for cassava roots. Here, we introduce a set of new variables and methods to phenotype cassava roots and enhance breeding pipelines.

METHODS

Different cassava genotypes were planted in pot and field conditions under well-watered and drought treatments. We developed cassava shovelomics and used digital imaging of root traits (DIRT) to evaluate geometrical root traits in addition to common traits (e.g., length, number).

RESULTS

Cassava shovelomics and DIRT were successfully implemented to extract root phenotypes, and a large phenotypic variation for root traits was observed. Significant correlations were found among root traits measured manually and by DIRT. Drought significantly decreased shoot dry weight, total root number, and root length by 84%, 30%, and 25%, respectively. High adventitious root number was associated with increased shoot dry weight (r = 0.44) under drought.

DISCUSSION

Our methods allow for high-throughput cassava root phenotyping, which makes a breeding program targeting root traits feasible. We suggest that root number is a breeding target for improved cassava production under drought.

Uncovering the hidden half of plants using new advances in root phenotyping

Major increases in crop yield are required to keep pace with population growth and climate change. Improvements to the architecture of crop roots promise to deliver increases in water and nutrient use efficiency but profiling the root phenome (i.e. its structure and function) represents a major bottleneck. We describe how advances in imaging and sensor technologies are making root phenomic studies possible. However, methodological advances in acquisition, handling and processing of the resulting 'big-data' is becoming increasingly important. Advances in automated image analysis approaches such as Deep Learning promise to transform the root phenotyping landscape. Collectively, these innovations are helping drive the selection of the next-generation of crops to deliver real world impact for ongoing global food security efforts.

Automating measurements of fluorescent signals in freely moving plant leaf specimens

Existing methods to quantify fluorescent signals are primarily limited to non-moving objects or tracking a limited number of cells. These techniques, however, are unsuitable for measuring fluorescent signals in time-lapse experiments using plant specimens that move naturally during a course of imaging. We developed an automated method to measure fluorescent signal intensities in transgenic Arabidopsis plants using a stereomicroscope with standard microscopy software. The features of our technique include: 1) recognizing the shape of plant specimens using autofluorescent signals; 2) merging targeted fluorescent signals to specimen outlines; 3) extracting signals within the shape of specimens from their background signals. Our method facilitates the measurement of fluorescent signals on freely moving plant leaves that are physically unrestrained. The method we developed addresses the challenge of recognizing plant shapes without relying on: a) manual definition which is prone to subjectivity and human error; b) introducing stable fluorescent markers to define plant shapes; c) recognizing plant shapes from bright field images which include a wide range of colors and background noise; d) unnecessarily stressing plants by immobilizing them; e) the use of multiple software packages or software development expertise.

HY5 Contributes to Light-Regulated Root System Architecture Under a Root-Covered Culture System

Light is essential for plant organogenesis and development. Light-regulated shoot morphogenesis has been extensively studied; however, the mechanisms by which plant roots perceive and respond to aboveground light are largely unknown, particularly because the roots of most terrestrial plants are usually located underground in darkness. To mimic natural root growth conditions, we developed a root-covered system (RCS) in which the shoots were illuminated and the plant roots could be either exposed to light or cultivated in darkness. Using the RCS, we observed that root growth of wild-type plants was significantly promoted when the roots were in darkness, whereas it was inhibited by direct light exposure. This growth change seems to be regulated by ELONGATED HYPOCOTYL 5 (HY5), a master regulator of photomorphogenesis. Light was found to regulate HY5 expression in the roots, while a HY5 deficiency partially abolished the inhibition of growth in roots directly exposed to light, suggesting that HY5 expression is induced by direct light exposure and inhibits root growth. However, no differences in HY5 expression were observed between illuminated and dark-grown cop1 roots, indicating that HY5 may be regulated by COP1-mediated proteasome degradation. We confirmed the crucial role of HY5 in regulating root development in response to light under soil-grown conditions. A transcriptomic analysis revealed that light controls the expression of numerous genes involved in phytohormone signaling, stress adaptation, and metabolic processes in a HY5-dependent manner. In combination with the results of the flavonol quantification and exogenous quercetin application, these findings suggested that HY5 regulates the root response to light through a complex network that integrates flavonol biosynthesis and reactive oxygen species signaling. Collectively, our results indicate that HY5 is a master regulator of root photomorphogenesis.